| Literature DB >> 29467215 |
Dan-Dan Tian1, Joshua J Kellogg1, Neşe Okut1, Nicholas H Oberlies1, Nadja B Cech1, Danny D Shen1, Jeannine S McCune1, Mary F Paine2.
Abstract
Green tea (Camellia sinensis) is a popular beverage worldwide, raising concern for adverse interactions when co-consumed with conventional drugs. Like many botanical natural products, green tea contains numerous polyphenolic constituents that undergo extensive glucuronidation. As such, the UDP-glucuronosyltransferases (UGTs), particularly intestinal UGTs, represent potential first-pass targets for green tea-drug interactions. Candidate intestinal UGT inhibitors were identified using a biochemometrics approach, which combines bioassay and chemometric data. Extracts and fractions prepared from four widely consumed teas were screened (20-180 μg/ml) as inhibitors of UGT activity (4-methylumbelliferone glucuronidation) in human intestinal microsomes; all demonstrated concentration-dependent inhibition. A biochemometrics-identified fraction rich in UGT inhibitors from a representative tea was purified further and subjected to second-stage biochemometric analysis. Five catechins were identified as major constituents in the bioactive subfractions and prioritized for further evaluation. Of these catechins, (-)-epicatechin gallate and (-)-epigallocatechin gallate showed concentration-dependent inhibition, with IC50 values (105 and 59 μM, respectively) near or below concentrations measured in a cup (240 ml) of tea (66 and 240 μM, respectively). Using the clinical intestinal UGT substrate raloxifene, the Ki values were ∼1.0 and 2.0 μM, respectively. Using estimated intestinal lumen and enterocyte inhibitor concentrations, a mechanistic static model predicted green tea to increase the raloxifene plasma area under the curve up to 6.1- and 1.3-fold, respectively. Application of this novel approach, which combines biochemometrics with in vitro-in vivo extrapolation, to other natural product-drug combinations will refine these procedures, informing the need for further evaluation via dynamic modeling and clinical testing.Entities:
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Year: 2018 PMID: 29467215 PMCID: PMC5890833 DOI: 10.1124/dmd.117.079491
Source DB: PubMed Journal: Drug Metab Dispos ISSN: 0090-9556 Impact factor: 3.922